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Information Journal Paper

Title

A MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION

Pages

  75-88

Abstract

 This paper deals with RIDGE ESTIMATION of FUZZY NONPARAMETRIC REGRESSION models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the LOCAL LINEAR SMOOTHING technique with the cross- validation procedure for selecting the optimal value of the smoothing param- eter is fuzzified to fit the presented model. Some simulation experiments are then presented which indicate the performance of the proposed method.

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    • Cite

    APA: Copy

    FARNOOSH, R., GHASEMIAN, J., & SOLAYMANI FARD, O.. (2012). A MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION. IRANIAN JOURNAL OF FUZZY SYSTEMS, 9(2), 75-88. SID. https://sid.ir/paper/576400/en

    Vancouver: Copy

    FARNOOSH R., GHASEMIAN J., SOLAYMANI FARD O.. A MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2012;9(2):75-88. Available from: https://sid.ir/paper/576400/en

    IEEE: Copy

    R. FARNOOSH, J. GHASEMIAN, and O. SOLAYMANI FARD, “A MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 9, no. 2, pp. 75–88, 2012, [Online]. Available: https://sid.ir/paper/576400/en

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